# Signal processing

Basic processing procedures for time series (e.g., performing a z-score of a
signal, or filtering a signal).

`zscore` (signal[, inplace]) |
Apply a z-score operation to one or several neo.AnalogSignal objects. |

`cross_correlation_function` (signal, channel_pairs) |
Computes an estimator of the cross-correlation function [sig1]. |

`butter` (signal[, highpass_frequency, ...]) |
Butterworth filtering function for neo.AnalogSignal. |

`wavelet_transform` (signal, frequency[, ...]) |
Compute the wavelet transform of a given signal with Morlet mother wavelet. |

`hilbert` (signal[, padding]) |
Apply a Hilbert transform to a neo.AnalogSignal object in order to obtain its (complex) analytic signal. |

`rauc` (signal[, baseline, bin_duration, ...]) |
Calculate the rectified area under the curve (RAUC) for a neo.AnalogSignal. |

`derivative` (signal) |
Calculate the derivative of a neo.AnalogSignal. |

## References

[sig1] | Petre Stoica, Randolph L Moses, and others. Spectral analysis of signals. *Prentice Hall*, 2005. |

[sig2] | Michel Le Van Quyen, Jack Foucher, Jean-Philippe Lachaux, Eugenio Rodriguez, Antoine Lutz, Jacques Martinerie, and Francisco J Varela. Comparison of hilbert transform and wavelet methods for the analysis of neuronal synchrony. *Journal of neuroscience methods*, 111(2):83–98, 2001. |

[sig3] | Marie Farge. Wavelet transforms and their applications to turbulence. *Annual review of fluid mechanics*, 24(1):395–458, 1992. |